A real-time strain monitoring framework for UAV wings based on a dual-driven approach integrating physical models and data
Year: 2025
Type: article
Abstract: With the increasing prevalence of drone applications, monitoring their health status has become crucial. This paper compares the prediction accuracy and spatial range of predictions between data-driven and dual-driven methods, which combine models and data. A real-time strain monitoring framework for UAV wings based on a dual-driven approach integrating physical models and data is proposed. This framework overcomes the limitations of single-method approaches and keeps prediction errors within 10%. Additionally, by utilizing real-time data from sensors and visualizing the predicted wing model, real-time monitoring of UAV wing strain is achieved. This provides a robust safeguard for the safe flight and mission execution of UAVs.
Authors: Donglin Wu, Xuechen Liu, Ling Zhou
Institution: Nanchang Hangkong University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412818870